similar to: Mixed model question

Hi again, thank you for your previous answers. Just another question, though ... I get the following variance components after fitting a mixed model. Groups Name Variance Std.Dev. Corr PlantID TreatmCtrl 0.51784 0.71961 TreatmNoAccess 4.77469 2.18511 -0.063 TreatmNoKeel 4.22726 2.05603 0.513 0.751 TreatmNoSpur 0.45918

Dear R-users, the problem I'm facing today is to write a multicolor main title in a plot. I would like to have 3/4 colors to help people in the audience to visually realize what is what in a 4x2 plot array On top of each plot I would like to have two lines. The 1st line will indicate what is plotted The 2nd line will indicate a a reference Graphically speaking I would like a result similar

Hello all R-user I am relative new to the R-environment and also to GLMM, so please don't be irritated if some questions don't make sense. I am using R 2.0.0 on Windows 2000. I investigated the occurrence of insects (count) in different parts of different plants (plantid) and recorded as well some characteristics of the plant parts (e.g. thickness). It is an unbalanced design with 21

Dear all,   I have data from the following experimental design and trying to fit a mixed model with lme function according to following steps but struggling. Any help is deeply appreciated.   1) Experimental design: I have 40 plants each of which has 4 clones. Each clone planted to one of 4 blocks. Phenotypes were collected from each clone for 3 consecutive years. I have genotypes of plants. I

Hello R list, I am hoping to conduct a logistic regression with repeated measures, and would love an actual "code run through" for such an analysis. I found only one related post on this list, but a full answer was never provided. I understand that the routine lmer (or lmer2) in the lme4 package is often recommended in such a case, but actually implementing it is where I've hit a

Dear list, I am new to this list and I am new to the world of R. Additionally I am not very firm in statistics either but have to deal. So here is my problem: I have a dataset (which I attach at the end of the post) with a binomial response variable (alive or not) and three fixed factors (trapping,treat,sex). I do have repeated measures and would like to include one (enclosure) random factor. I

Dear all, For my research I need to perform a Levene's test on my data.I have not large experience with this test and with R,so I have some problems to use the leveneTest function. I read some previous posts on this topic but I cannot understand what I have to do. I have a five-columns data frame organised in the following way: number of observation, number of subject, score, type of

This concerns whether p-values from lmer can be trusted. From simulations, it seems that lmer can produce very small, and probably spurious, p-values. I realize that lmer is not yet a finished product. Is it likely that the problem will be fixed in a future release of the lme4 package? Using simulated data for a quite standard mixed-model anova (a balanced two-way design; see code for the

Hi, I am looking for a way to analyze a dataset with a circular dependent variable and three independent factors. To be specific, the circular variable comprises of arrival times of pollinators to flowers. The independent variables are pollinator species, flower sex and locality. I have failed to find a way how to include all three factors. The "circular" package seems to enable testing

Hi All, I am trying to shift from running mixed models in SAS using PROC MIXED to using lme4 package in R. In trying to match the coefficients of R output to that of SAS output, I came across this problem. The dataset I am using is this one: http://support.sas.com/documentation/cdl/en/statug/63033/HTML/default/viewer.htm#statug_mixed_sect034.htm If I run the following code: proc mixed data=rc

Hi I am trying to convert SAS codes to R, but some of the result are quite different from SAS. When I ran proc mixed, I have an option ddfm=bw followed by the model. How can I show this method in R?(I am thinking that this maybe the reason that I can't get the similar results) below is my SAS codes: proc mixed data=test covtest empirical; class pair grade team school; model score = trt

Hi all! Just wondering if anyone has successfully used puppet in combination with NSIS installers (afaik only msi support is available at the moment - i''m not yet familiar with puppet''s capabilities under windows systems). Thank you very much in advance, Pedro Lafuente -- You received this message because you are subscribed to the Google Groups "Puppet Users"

Dear R-gurus, I am pretty much new on R. I am trying to to do a repeated analysis of a linear mixed model with R, and I consistently fail... The problem is: Cow is the random factor, treatment is the fixed factor. The dependent variable is milk yield, which is measured several times (repeatedly over time), thus there is another variable which is time (i.e. week). The model would be

Hi All, I'm working with some SAS code to analyze an experiment set up as follows: 66 subjects (colonies) treated with a random treatment (1-8) and measured at three time points. The data structure looks like: input colony tmt y1 y2 y3; y=y1; date=*1*; output; y=y2; date=*2*; output; y=y3; date=*3*; output; datalines; 1

R users, What is the equivalent of SAS " '/diff' and '/slice'" in R ? I am successful in fitting the same model "PROC MIXED" fits using lme() : ###R code: model <- lme( y ~ g + h + yr + yr:h, random = ~ 1 | b, data = yield) *** SAS code: proc mixed data=yield covtest cl method=reml; class b g h yr; model y = g h yr yr*h; random b; lsmeans g / diff;

Does anyone know of R functions for doing composite quantile regression (Hou and Yuan Ann Stat 36:1108, 2008)? The paper's authors do not talk about software in their paper or on their web sites. Thanks Frank ----- Frank Harrell Department of Biostatistics, Vanderbilt University -- View this message in context: http://r.789695.n4.nabble.com/Composite-Quantile-Regression-tp4663463.html

Hello, I am very new to R (as my Subject probably indicates). I want to do something that should, I think, be very simple. I have five vectors in a list and I want to construct a covariance matrix out of them. Given a 5X5 matrix cvm1, and the list of vectors, cvm1_list, I thought the following would work (sorry cannot find code tags): for(i in 1:5){ for(j in 1:5){ cvm1[i,j] <-

Hi All I am trying to translate a proc mixed into a lme() syntax. It seems that I was able to do it for part of the model, but a few things are still different. It is a 2-level bivariate model (some call it a pseudo-3-level model). PROC MIXED DATA=psdata.bivar COVTEST METHOD = ml; CLASS cluster_ID individual_id variable_id ; MODEL y = Dp Dq / SOLUTION NOINT; RANDOM Dp Dq / SUBJECT = cluster_ID

Please help us by spreading the word to your communities! Blog post with attachments at http://ur1.ca/3vw3t ### Help Keep LGM Free for Developers and Artists Your contribution can help make Libre Graphics Meeting 2011 (LGM) a success! All funds donated by the community to the LGM 2011 Pledgie campaign go directly towards providing travel reimbursement to the developers of free graphics

Hi, I've tried to make toll-free DID work for the last 2-3 weeks. Apparently only the IAX.CC/Sixtel personnel can make a call to my toll-free. Anybody else just gets a busy signal. It takes for them about 5-6 business days to respond to my request. It seems they are looking in the once a week to the High priority tickets. It also seems that they are permanently closed ! No matter when I